Dennis Fox

The relationship of soil loss by interrill erosion to slope gradient

Abstract The influence of slope gradient on erosion rate differs for rill and interrill conditions. Rill erosion increases substantially more with increasing slope gradient than interrill erosion. Combining the two erosion processes into single data sets led to the development of regression equations (e.g., USLE) that overestimated the effect of slope gradient on erosion rate for low slope gradients and short slopes. This study investigated the change in interrill erosion rate with slope gradient and examined its relationship to runoff velocity. A sandy loam (grey brown luvisol) was packed in 100×40×10 cm3 soil trays and subjected to simulated rainfall for a period of 75 min. Rain-impacted flow erosion and downslope splash were monitored, and runoff velocity measurements were made at three positions within the flume. Downslope splash erosion never accounted for more than 20% of the total erosion. Rain-impacted flow erosion peaked early in the simulation then decreased to a constant rate; erosion rate was therefore probably detachment-limited. For a constant runoff rate, rain-impacted flow erosion increased roughly with the square root of slope gradient, as did the runoff velocity. Soil loss was correlated (0.81) with runoff velocity under the experimental conditions.

Predicting Land Cover Change in a Mediterranean Catchment at Different Time Scales

Land cover has been changing rapidly throughout the world, and this issue is important to researchers, urban planners, and ecologists for sustainable land cover planning for the future. Many modeling tools have been developed to explore and evaluate possible land cover scenarios in future and time scales vary greatly from one study to another. The main objective of this study is to test land cover change prediction at different time scales in a Mediterranean catchment in SE France. Land cover maps were created from aerial photographs (1950, 1982, 2003, 2008, and 2011) of the Giscle catchment (235 Km2) and surfaces were classified into four land cover categories: forest, vineyard, grassland, and built area. Explanatory variables were selected through Cramer’s coefficient. Different time scales were tested in the study: short (2003-2008), intermediate (1982-2003), and long (1950-1982). To test the model’s accuracy, Land Change Modeler (LCM) of IDRISI was used to predict land cover in 2011 and predicted images were compared to a real 2011 map. Kappa index and confusion matrix were used to evaluate the model’s accuracy. Altitude, slope, and distance from roads had the greatest impact on land cover changes among all variables tested. Good to perfect level of spatial and perfect level of quantitative agreement were observed in long to short time scale simulations. Kappa indices (Kquantity = 0.99and Klocation = 0.90) and confusion matrices were good for intermediate and best for short time scale. The results indicate that shorter time scales produce better predictions. Time scale effects have strong interactions with specific land cover dynamics, in which stable land covers are easier to predict than cases of rapid change and quantity is easier to predict than location for longer time periods.

Spatial dynamics of land cover change in a Euro-Mediterranean catchment (1950–2008)

The Euro-Mediterranean area has experienced widespread land cover change since 1950, but few studies of land cover change explicitly explore spatial constraints on land cover change patterns. The main objective of this study was to analyze the spatial dynamics of land cover change from 1950 to 2008 in a French Mediterranean catchment. Aerial photographs (1950, 1982, and 2008) were screen digitized, and surfaces were classified into five categories: forest, vineyard, grassland, urban, and suburban. Land cover changes were concentrated mainly in the alluvial plain. Although forest remained the dominant land cover in the catchment (>85.0%), it underwent significant swapping with vineyard and grassland. Vineyard decreased (34% of initial loss) while grassland increased (43% of initial). Urban and suburban areas remained minor in the catchment (0.2% in 1950 and 3.0% in 2008), but showed a dramatic relative increase (about 20×). Changes occurred mainly at low altitudes and slopes. Vineyard located near streams was converted mainly to grassland. Built areas were dependent on roads and former built areas for expansion but expanded little near streams due to flooding risks. The rate of change was greater during the latter part of the study (1982–2008) than in the earlier phase (1950–1982).